Hybrid algorithm based on genetic algorithm and PSO for task scheduling in cloud computing environment Online publication date: Sun, 30-Jul-2017
by A. Kousalya; R. Radhakrishnan
International Journal of Networking and Virtual Organisations (IJNVO), Vol. 17, No. 2/3, 2017
Abstract: The cloud computing enable the user to run their applications in remote data centres. Parallel processing solves the complexity of the application and it focus on improving responsiveness and utilisation. However, most existing task-scheduling methods do not considers the bandwidth requirements rather they consider task resource requirements for CPU and memory. In this paper, a novel task allocation model is proposed for the divisible task-scheduling. Foreground and background are the two partition of virtual machine based on the quantity of node. In order to achieve the optimised task allocation an optimisation algorithm (improved genetic algorithm) is implemented along with the foreground and background process. The optimised allocation scheme that determines proper number of tasks assigned to each virtual resource node is obtained.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Networking and Virtual Organisations (IJNVO):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com